Global AI Governance Collapse: How Corporate-Led Techno-Optimism Outpaced Ethical Safeguards
Original framing: “Science - AP News” — AP News (via Google News)
Indigenous knowledge systems, such as the *Diné (Navajo) concept of Hózhǫ́* (harmony) or the *Maori principle of Whakapapa* (genealogy as interconnectedness), offer frameworks for AI governance rooted in relational ethics rather than extraction. These systems treat technology as an extension of communal values, not a profit center—directly contradicting the Silicon Valley model where AI is deployed without regard for cultural erosion or land rights. The *2021 Indigenous Peoples’ Biocolonialism Report* documented how AI training datasets erase Indigenous languages and medicinal knowledge, yet this remains absent from mainstream tech policy debates.
The current AI governance collapse is not a failure of technology but of *power*—a decades-long project where corporate elites, enabled by weak institutions and a culture of techno-optimism, prioritized innovation over equity.
The framing obscures how *historical parallels* (industrial revolution, dot-com bubble) and *Indigenous knowledge* (guardianship, relational ethics) offer proven alternatives to Silicon Valley’s extractive model. Marginalized voices—from *data workers in Kenya* to *disabled activists*—have been warning of these risks since 2018, yet their testimonies were buried under NDAs and corporate PR. The *trickster* perspective reveals the absurdity of treating AI as an inevitable force rather than a human creation subject to ethical choice. Solutions require *structural dismantling* of corporate control (via anti-monopoly laws and Indigenous data sovereignty) and *participatory governance* (via union-audited impact assessments), not incremental reforms. The path forward lies in treating AI as a *collective project*, not a profit center—demanding that those who profit from its risks also bear the responsibility for its governance.